Whisper-small-thai / README.md
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metadata
license: apache-2.0
base_model: biodatlab/whisper-th-small-combined
tags:
  - generated_from_trainer
datasets:
  - common_voice_17_0
metrics:
  - wer
model-index:
  - name: Whisper-small-thai
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_17_0
          type: common_voice_17_0
          config: th
          split: test
          args: th
        metrics:
          - name: Wer
            type: wer
            value: 55.432891743610334

Whisper-small-thai

This model is a fine-tuned version of biodatlab/whisper-th-small-combined on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1073
  • Wer: 55.4329

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3415 0.3647 1000 0.1371 65.4958
0.1638 0.7294 2000 0.1253 60.3238
0.1995 1.0941 3000 0.1161 57.4736
0.213 1.4588 4000 0.1104 56.2358
0.2041 1.8235 5000 0.1073 55.4329

Framework versions

  • Transformers 4.43.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1